Andrzej Daniluk, Evgeny Lakshtanov, Rafal Muchorski
{"title":"Denoised Monte Carlo for option pricing and Greeks estimation","authors":"Andrzej Daniluk, Evgeny Lakshtanov, Rafal Muchorski","doi":"arxiv-2402.12528","DOIUrl":null,"url":null,"abstract":"We present a novel technique of Monte Carlo error reduction that finds direct\napplication in option pricing and Greeks estimation. The method is applicable\nto any LSV modelling framework and concerns a broad class of payoffs, including\npath-dependent and multi-asset cases. Most importantly, it allows to reduce the\nMonte Carlo error even by an order of magnitude, which is shown in several\nnumerical examples.","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Pricing of Securities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2402.12528","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We present a novel technique of Monte Carlo error reduction that finds direct
application in option pricing and Greeks estimation. The method is applicable
to any LSV modelling framework and concerns a broad class of payoffs, including
path-dependent and multi-asset cases. Most importantly, it allows to reduce the
Monte Carlo error even by an order of magnitude, which is shown in several
numerical examples.
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